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Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise
| Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (366 p.) |
| Disciplina |
572.8636
572.865 |
| Altri autori (Persone) |
DoKim-Anh <1960->
AmbroiseChristophe <1969-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Gene expression - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-25332-0
9786610253326 0-470-35030-X 0-471-72612-5 0-471-72842-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analyzing Microarray Gene Expression Data; Contents; Preface; 1 Microarrays in Gene Expression Studies; 1.1 Introduction; 1.2 Background Biology; 1.2.1 Genome, Genotype, and Gene Expression; 1.2.2 Of Wild-Types and Other Alleles; 1.2.3 Aspects of Underlying Biology and Physiochemistry; 1.3 Polymerase Chain Reaction; 1.4 cDNA; 1.4.1 Expressed Sequence Tag; 1.5 Microarray Technology and Application; 1.5.1 History of Microarray Development; 1.5.2 Tools of Microarray Technology; 1.5.3 Limitations of Microarray Technology; 1.5.4 Oligonucleotides versus cDNA Arrays
1.5.5 SAGE: Another Method for Detecting and Measuring Gene Expression Levels1.5.6 Emerging Technologies; 1.6 Sampling of Relevant Research Entities and Public Resources; 2 Cleaning and Normalization; 2.1 Introduction; 2.2 Cleaning Procedures; 2.2.1 Image Processing to Extract Information; 2.2.2 Missing Value Estimation; 2.2.3 Sources of Nonlinearity; 2.3 Normalization and Plotting Procedures for Oligonucleotide Arrays; 2.3.1 Global Approaches for Oligonucleotide Array Data; 2.3.2 Spiked Standard Approaches; 2.3.3 Geometric Mean and Linear Regression Normalization for Multiple Arrays 2.3.4 Nonlinear Normalization for Multiple Arrays Using Smooth Curves2.4 Normalization Methods for cDNA Microarray Data; 2.4.1 Single-Array Normalization; 2.4.2 Multiple Slides Normalization; 2.4.3 ANOVA and Related Methods for Normalization; 2.4.4 Mixed-Model Method for Normalization; 2.4.5 SNOMAD; 2.5 Transformations and Replication; 2.5.1 Importance of Replication; 2.5.2 Transformations; 2.6 Analysis of the Alon Data Set; 2.7 Comparison of Normalization Strategies and Discussion; 3 Some Cluster Analysis Methods; 3.1 Introduction; 3.2 Reduction in the Dimension of the Feature Space 3.3 Cluster Analysis3.4 Some Hierarchical Agglomerative Techniques; 3.5 k-Means Clustering; 3.6 Cluster Analysis with No A Priori Metric; 3.7 Clustering via Finite Mixture Models; 3.7.1 Definition; 3.7.2 Advantages of Model-Based Clustering; 3.8 Fitting Mixture Models Via the EM Algorithm; 3.8.1 E-Step; 3.8.2 M-Step; 3.8.3 Choice of Starting Values for the EM Algorithm; 3.9 Clustering Via Normal Mixtures; 3.9.1 Heteroscedastic Components; 3.9.2 Homoscedastic Components; 3.9.3 Spherical Components; 3.9.4 Choice of Root; 3.9.5 Available Software; 3.10 Mixtures of t Distributions 3.11 Mixtures of Factor Analyzers3.12 Choice of Clustering Solution; 3.13 Classification ML Approach; 3.14 Mixture Models for Clinical and Microarray Data; 3.14.1 Unconditional Approach; 3.14.2 Conditional Approach; 3.15 Choice of the Number of Components in a Mixture Model; 3.15.1 Order of a Mixture Model; 3.15.2 Approaches for Assessing Mixture Order; 3.15.3 Bayesian Information Criterion; 3.15.4 Integrated Classification Likelihood Criterion; 3.16 Resampling Approach; 3.17 Other Resampling Approaches for Number of Clusters; 3.17.1 The Gap Statistic 3.17.2 The Clest Method for the Number of Clusters |
| Record Nr. | UNINA-9910146082203321 |
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise
| Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (366 p.) |
| Disciplina |
572.8636
572.865 |
| Altri autori (Persone) |
DoKim-Anh <1960->
AmbroiseChristophe <1969-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Gene expression - Statistical methods |
| ISBN |
1-280-25332-0
9786610253326 0-470-35030-X 0-471-72612-5 0-471-72842-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analyzing Microarray Gene Expression Data; Contents; Preface; 1 Microarrays in Gene Expression Studies; 1.1 Introduction; 1.2 Background Biology; 1.2.1 Genome, Genotype, and Gene Expression; 1.2.2 Of Wild-Types and Other Alleles; 1.2.3 Aspects of Underlying Biology and Physiochemistry; 1.3 Polymerase Chain Reaction; 1.4 cDNA; 1.4.1 Expressed Sequence Tag; 1.5 Microarray Technology and Application; 1.5.1 History of Microarray Development; 1.5.2 Tools of Microarray Technology; 1.5.3 Limitations of Microarray Technology; 1.5.4 Oligonucleotides versus cDNA Arrays
1.5.5 SAGE: Another Method for Detecting and Measuring Gene Expression Levels1.5.6 Emerging Technologies; 1.6 Sampling of Relevant Research Entities and Public Resources; 2 Cleaning and Normalization; 2.1 Introduction; 2.2 Cleaning Procedures; 2.2.1 Image Processing to Extract Information; 2.2.2 Missing Value Estimation; 2.2.3 Sources of Nonlinearity; 2.3 Normalization and Plotting Procedures for Oligonucleotide Arrays; 2.3.1 Global Approaches for Oligonucleotide Array Data; 2.3.2 Spiked Standard Approaches; 2.3.3 Geometric Mean and Linear Regression Normalization for Multiple Arrays 2.3.4 Nonlinear Normalization for Multiple Arrays Using Smooth Curves2.4 Normalization Methods for cDNA Microarray Data; 2.4.1 Single-Array Normalization; 2.4.2 Multiple Slides Normalization; 2.4.3 ANOVA and Related Methods for Normalization; 2.4.4 Mixed-Model Method for Normalization; 2.4.5 SNOMAD; 2.5 Transformations and Replication; 2.5.1 Importance of Replication; 2.5.2 Transformations; 2.6 Analysis of the Alon Data Set; 2.7 Comparison of Normalization Strategies and Discussion; 3 Some Cluster Analysis Methods; 3.1 Introduction; 3.2 Reduction in the Dimension of the Feature Space 3.3 Cluster Analysis3.4 Some Hierarchical Agglomerative Techniques; 3.5 k-Means Clustering; 3.6 Cluster Analysis with No A Priori Metric; 3.7 Clustering via Finite Mixture Models; 3.7.1 Definition; 3.7.2 Advantages of Model-Based Clustering; 3.8 Fitting Mixture Models Via the EM Algorithm; 3.8.1 E-Step; 3.8.2 M-Step; 3.8.3 Choice of Starting Values for the EM Algorithm; 3.9 Clustering Via Normal Mixtures; 3.9.1 Heteroscedastic Components; 3.9.2 Homoscedastic Components; 3.9.3 Spherical Components; 3.9.4 Choice of Root; 3.9.5 Available Software; 3.10 Mixtures of t Distributions 3.11 Mixtures of Factor Analyzers3.12 Choice of Clustering Solution; 3.13 Classification ML Approach; 3.14 Mixture Models for Clinical and Microarray Data; 3.14.1 Unconditional Approach; 3.14.2 Conditional Approach; 3.15 Choice of the Number of Components in a Mixture Model; 3.15.1 Order of a Mixture Model; 3.15.2 Approaches for Assessing Mixture Order; 3.15.3 Bayesian Information Criterion; 3.15.4 Integrated Classification Likelihood Criterion; 3.16 Resampling Approach; 3.17 Other Resampling Approaches for Number of Clusters; 3.17.1 The Gap Statistic 3.17.2 The Clest Method for the Number of Clusters |
| Record Nr. | UNINA-9910830637803321 |
|
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analyzing microarray gene expression data / / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise
| Analyzing microarray gene expression data / / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (366 p.) |
| Disciplina | 572.8/636 |
| Altri autori (Persone) |
DoKim-Anh <1960->
AmbroiseChristophe <1969-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Gene expression - Statistical methods |
| ISBN |
1-280-25332-0
9786610253326 0-470-35030-X 0-471-72612-5 0-471-72842-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analyzing Microarray Gene Expression Data; Contents; Preface; 1 Microarrays in Gene Expression Studies; 1.1 Introduction; 1.2 Background Biology; 1.2.1 Genome, Genotype, and Gene Expression; 1.2.2 Of Wild-Types and Other Alleles; 1.2.3 Aspects of Underlying Biology and Physiochemistry; 1.3 Polymerase Chain Reaction; 1.4 cDNA; 1.4.1 Expressed Sequence Tag; 1.5 Microarray Technology and Application; 1.5.1 History of Microarray Development; 1.5.2 Tools of Microarray Technology; 1.5.3 Limitations of Microarray Technology; 1.5.4 Oligonucleotides versus cDNA Arrays
1.5.5 SAGE: Another Method for Detecting and Measuring Gene Expression Levels1.5.6 Emerging Technologies; 1.6 Sampling of Relevant Research Entities and Public Resources; 2 Cleaning and Normalization; 2.1 Introduction; 2.2 Cleaning Procedures; 2.2.1 Image Processing to Extract Information; 2.2.2 Missing Value Estimation; 2.2.3 Sources of Nonlinearity; 2.3 Normalization and Plotting Procedures for Oligonucleotide Arrays; 2.3.1 Global Approaches for Oligonucleotide Array Data; 2.3.2 Spiked Standard Approaches; 2.3.3 Geometric Mean and Linear Regression Normalization for Multiple Arrays 2.3.4 Nonlinear Normalization for Multiple Arrays Using Smooth Curves2.4 Normalization Methods for cDNA Microarray Data; 2.4.1 Single-Array Normalization; 2.4.2 Multiple Slides Normalization; 2.4.3 ANOVA and Related Methods for Normalization; 2.4.4 Mixed-Model Method for Normalization; 2.4.5 SNOMAD; 2.5 Transformations and Replication; 2.5.1 Importance of Replication; 2.5.2 Transformations; 2.6 Analysis of the Alon Data Set; 2.7 Comparison of Normalization Strategies and Discussion; 3 Some Cluster Analysis Methods; 3.1 Introduction; 3.2 Reduction in the Dimension of the Feature Space 3.3 Cluster Analysis3.4 Some Hierarchical Agglomerative Techniques; 3.5 k-Means Clustering; 3.6 Cluster Analysis with No A Priori Metric; 3.7 Clustering via Finite Mixture Models; 3.7.1 Definition; 3.7.2 Advantages of Model-Based Clustering; 3.8 Fitting Mixture Models Via the EM Algorithm; 3.8.1 E-Step; 3.8.2 M-Step; 3.8.3 Choice of Starting Values for the EM Algorithm; 3.9 Clustering Via Normal Mixtures; 3.9.1 Heteroscedastic Components; 3.9.2 Homoscedastic Components; 3.9.3 Spherical Components; 3.9.4 Choice of Root; 3.9.5 Available Software; 3.10 Mixtures of t Distributions 3.11 Mixtures of Factor Analyzers3.12 Choice of Clustering Solution; 3.13 Classification ML Approach; 3.14 Mixture Models for Clinical and Microarray Data; 3.14.1 Unconditional Approach; 3.14.2 Conditional Approach; 3.15 Choice of the Number of Components in a Mixture Model; 3.15.1 Order of a Mixture Model; 3.15.2 Approaches for Assessing Mixture Order; 3.15.3 Bayesian Information Criterion; 3.15.4 Integrated Classification Likelihood Criterion; 3.16 Resampling Approach; 3.17 Other Resampling Approaches for Number of Clusters; 3.17.1 The Gap Statistic 3.17.2 The Clest Method for the Number of Clusters |
| Record Nr. | UNINA-9910877596703321 |
|
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The EM algorithm and extensions [[electronic resource] /] / Geoffrey J. McLachlan, Thriyambakam Krishnan
| The EM algorithm and extensions [[electronic resource] /] / Geoffrey J. McLachlan, Thriyambakam Krishnan |
| Autore | McLachlan Geoffrey J. <1946-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2008 |
| Descrizione fisica | 1 online resource (399 p.) |
| Disciplina |
519.5
519.5/44 519.544 |
| Altri autori (Persone) | KrishnanT <1938-> (Thriyambakam) |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Expectation-maximization algorithms
Estimation theory Missing observations (Statistics) |
| ISBN |
1-281-28447-5
9786611284473 0-470-19161-9 0-470-19160-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
The EM Algorithm and Extensions; CONTENTS; PREFACE TO THE SECOND EDITION; PREFACE TO THE FIRST EDITION; LIST OF EXAMPLES; 1 GENERAL INTRODUCTION; 1.1 Introduction; 1.2 Maximum Likelihood Estimation; 1.3 Newton-Type Methods; 1.3.1 Introduction; 1.3.2 Newton-Raphson Method; 1.3.3 Quasi-Newton Methods; 1.3.4 Modified Newton Methods; 1.4 Introductory Examples; 1.4.1 Introduction; 1.4.2 Example 1.1: A Multinomial Example; 1.4.3 Example 1.2: Estimation of Mixing Proportions; 1.5 Formulation of the EM Algorithm; 1.5.1 EM Algorithm; 1.5.2 Example 1.3: Censored Exponentially Distributed Survival Times
1.5.3 E- and M-Steps for the Regular Exponential Family1.5.4 Example 1.4: Censored Exponentially Distributed Survival Times (Example 1.3 Continued); 1.5.5 Generalized EM Algorithm; 1.5.6 GEM Algorithm Based on One Newton-Raphson Step; 1.5.7 EM Gradient Algorithm; 1.5.8 EM Mapping; 1.6 EM Algorithm for MAP and MPL Estimation; 1.6.1 Maximum a Posteriori Estimation; 1.6.2 Example 1.5: A Multinomial Example (Example 1.1 Continued); 1.6.3 Maximum Penalized Estimation; 1.7 Brief Summary of the Properties of the EM Algorithm; 1.8 History of the EM Algorithm; 1.8.1 Early EM History 1.8.2 Work Before Dempster, Laird, and Rubin (1977)1.8.3 EM Examples and Applications Since Dempster, Laird, and Rubin (1977); 1.8.4 Two Interpretations of EM; 1.8.5 Developments in EM Theory, Methodology, and Applications; 1.9 Overview of the Book; 1.10 Notations; 2 EXAMPLES OF THE EM ALGORITHM; 2.1 Introduction; 2.2 Multivariate Data with Missing Values; 2.2.1 Example 2.1: Bivariate Normal Data with Missing Values; 2.2.2 Numerical Illustration; 2.2.3 Multivariate Data: Buck's Method; 2.3 Least Squares with Missing Data; 2.3.1 Healy-Westmacott Procedure 2.3.2 Example 2.2: Linear Regression with Missing Dependent Values2.3.3 Example 2.3: Missing Values in a Latin Square Design; 2.3.4 Healy-Westmacott Procedure as an EM Algorithm; 2.4 Example 2.4: Multinomial with Complex Cell Structure; 2.5 Example 2.5: Analysis of PET and SPECT Data; 2.6 Example 2.6: Multivariate t-Distribution (Known D.F.); 2.6.1 ML Estimation of Multivariate t-Distribution; 2.6.2 Numerical Example: Stack Loss Data; 2.7 Finite Normal Mixtures; 2.7.1 Example 2.7: Univariate Component Densities; 2.7.2 Example 2.8: Multivariate Component Densities 2.7.3 Numerical Example: Red Blood Cell Volume Data2.8 Example 2.9: Grouped and Truncated Data; 2.8.1 Introduction; 2.8.2 Specification of Complete Data; 2.8.3 E-Step; 2.8.4 M-Step; 2.8.5 Confirmation of Incomplete-Data Score Statistic; 2.8.6 M-Step for Grouped Normal Data; 2.8.7 Numerical Example: Grouped Log Normal Data; 2.9 Example 2.10: A Hidden Markov AR(1) model; 3 BASIC THEORY OF THE EM ALGORITHM; 3.1 Introduction; 3.2 Monotonicity of the EM Algorithm; 3.3 Monotonicity of a Generalized EM Algorithm; 3.4 Convergence of an EM Sequence to a Stationary Value; 3.4.1 Introduction 3.4.2 Regularity Conditions of Wu (1983) |
| Record Nr. | UNINA-9910145008603321 |
|
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The EM algorithm and extensions [[electronic resource] /] / Geoffrey J. McLachlan, Thriyambakam Krishnan
| The EM algorithm and extensions [[electronic resource] /] / Geoffrey J. McLachlan, Thriyambakam Krishnan |
| Autore | McLachlan Geoffrey J. <1946-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2008 |
| Descrizione fisica | 1 online resource (399 p.) |
| Disciplina |
519.5
519.5/44 519.544 |
| Altri autori (Persone) | KrishnanT <1938-> (Thriyambakam) |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Expectation-maximization algorithms
Estimation theory Missing observations (Statistics) |
| ISBN |
1-281-28447-5
9786611284473 0-470-19161-9 0-470-19160-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
The EM Algorithm and Extensions; CONTENTS; PREFACE TO THE SECOND EDITION; PREFACE TO THE FIRST EDITION; LIST OF EXAMPLES; 1 GENERAL INTRODUCTION; 1.1 Introduction; 1.2 Maximum Likelihood Estimation; 1.3 Newton-Type Methods; 1.3.1 Introduction; 1.3.2 Newton-Raphson Method; 1.3.3 Quasi-Newton Methods; 1.3.4 Modified Newton Methods; 1.4 Introductory Examples; 1.4.1 Introduction; 1.4.2 Example 1.1: A Multinomial Example; 1.4.3 Example 1.2: Estimation of Mixing Proportions; 1.5 Formulation of the EM Algorithm; 1.5.1 EM Algorithm; 1.5.2 Example 1.3: Censored Exponentially Distributed Survival Times
1.5.3 E- and M-Steps for the Regular Exponential Family1.5.4 Example 1.4: Censored Exponentially Distributed Survival Times (Example 1.3 Continued); 1.5.5 Generalized EM Algorithm; 1.5.6 GEM Algorithm Based on One Newton-Raphson Step; 1.5.7 EM Gradient Algorithm; 1.5.8 EM Mapping; 1.6 EM Algorithm for MAP and MPL Estimation; 1.6.1 Maximum a Posteriori Estimation; 1.6.2 Example 1.5: A Multinomial Example (Example 1.1 Continued); 1.6.3 Maximum Penalized Estimation; 1.7 Brief Summary of the Properties of the EM Algorithm; 1.8 History of the EM Algorithm; 1.8.1 Early EM History 1.8.2 Work Before Dempster, Laird, and Rubin (1977)1.8.3 EM Examples and Applications Since Dempster, Laird, and Rubin (1977); 1.8.4 Two Interpretations of EM; 1.8.5 Developments in EM Theory, Methodology, and Applications; 1.9 Overview of the Book; 1.10 Notations; 2 EXAMPLES OF THE EM ALGORITHM; 2.1 Introduction; 2.2 Multivariate Data with Missing Values; 2.2.1 Example 2.1: Bivariate Normal Data with Missing Values; 2.2.2 Numerical Illustration; 2.2.3 Multivariate Data: Buck's Method; 2.3 Least Squares with Missing Data; 2.3.1 Healy-Westmacott Procedure 2.3.2 Example 2.2: Linear Regression with Missing Dependent Values2.3.3 Example 2.3: Missing Values in a Latin Square Design; 2.3.4 Healy-Westmacott Procedure as an EM Algorithm; 2.4 Example 2.4: Multinomial with Complex Cell Structure; 2.5 Example 2.5: Analysis of PET and SPECT Data; 2.6 Example 2.6: Multivariate t-Distribution (Known D.F.); 2.6.1 ML Estimation of Multivariate t-Distribution; 2.6.2 Numerical Example: Stack Loss Data; 2.7 Finite Normal Mixtures; 2.7.1 Example 2.7: Univariate Component Densities; 2.7.2 Example 2.8: Multivariate Component Densities 2.7.3 Numerical Example: Red Blood Cell Volume Data2.8 Example 2.9: Grouped and Truncated Data; 2.8.1 Introduction; 2.8.2 Specification of Complete Data; 2.8.3 E-Step; 2.8.4 M-Step; 2.8.5 Confirmation of Incomplete-Data Score Statistic; 2.8.6 M-Step for Grouped Normal Data; 2.8.7 Numerical Example: Grouped Log Normal Data; 2.9 Example 2.10: A Hidden Markov AR(1) model; 3 BASIC THEORY OF THE EM ALGORITHM; 3.1 Introduction; 3.2 Monotonicity of the EM Algorithm; 3.3 Monotonicity of a Generalized EM Algorithm; 3.4 Convergence of an EM Sequence to a Stationary Value; 3.4.1 Introduction 3.4.2 Regularity Conditions of Wu (1983) |
| Record Nr. | UNINA-9910831039703321 |
|
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The EM algorithm and extensions / / Geoffrey J. McLachlan, Thriyambakam Krishnan
| The EM algorithm and extensions / / Geoffrey J. McLachlan, Thriyambakam Krishnan |
| Autore | McLachlan Geoffrey J. <1946-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2008 |
| Descrizione fisica | 1 online resource (399 p.) |
| Disciplina | 519.5/44 |
| Altri autori (Persone) | KrishnanT <1938-> (Thriyambakam) |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Expectation-maximization algorithms
Estimation theory Missing observations (Statistics) |
| ISBN |
1-281-28447-5
9786611284473 0-470-19161-9 0-470-19160-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
The EM Algorithm and Extensions; CONTENTS; PREFACE TO THE SECOND EDITION; PREFACE TO THE FIRST EDITION; LIST OF EXAMPLES; 1 GENERAL INTRODUCTION; 1.1 Introduction; 1.2 Maximum Likelihood Estimation; 1.3 Newton-Type Methods; 1.3.1 Introduction; 1.3.2 Newton-Raphson Method; 1.3.3 Quasi-Newton Methods; 1.3.4 Modified Newton Methods; 1.4 Introductory Examples; 1.4.1 Introduction; 1.4.2 Example 1.1: A Multinomial Example; 1.4.3 Example 1.2: Estimation of Mixing Proportions; 1.5 Formulation of the EM Algorithm; 1.5.1 EM Algorithm; 1.5.2 Example 1.3: Censored Exponentially Distributed Survival Times
1.5.3 E- and M-Steps for the Regular Exponential Family1.5.4 Example 1.4: Censored Exponentially Distributed Survival Times (Example 1.3 Continued); 1.5.5 Generalized EM Algorithm; 1.5.6 GEM Algorithm Based on One Newton-Raphson Step; 1.5.7 EM Gradient Algorithm; 1.5.8 EM Mapping; 1.6 EM Algorithm for MAP and MPL Estimation; 1.6.1 Maximum a Posteriori Estimation; 1.6.2 Example 1.5: A Multinomial Example (Example 1.1 Continued); 1.6.3 Maximum Penalized Estimation; 1.7 Brief Summary of the Properties of the EM Algorithm; 1.8 History of the EM Algorithm; 1.8.1 Early EM History 1.8.2 Work Before Dempster, Laird, and Rubin (1977)1.8.3 EM Examples and Applications Since Dempster, Laird, and Rubin (1977); 1.8.4 Two Interpretations of EM; 1.8.5 Developments in EM Theory, Methodology, and Applications; 1.9 Overview of the Book; 1.10 Notations; 2 EXAMPLES OF THE EM ALGORITHM; 2.1 Introduction; 2.2 Multivariate Data with Missing Values; 2.2.1 Example 2.1: Bivariate Normal Data with Missing Values; 2.2.2 Numerical Illustration; 2.2.3 Multivariate Data: Buck's Method; 2.3 Least Squares with Missing Data; 2.3.1 Healy-Westmacott Procedure 2.3.2 Example 2.2: Linear Regression with Missing Dependent Values2.3.3 Example 2.3: Missing Values in a Latin Square Design; 2.3.4 Healy-Westmacott Procedure as an EM Algorithm; 2.4 Example 2.4: Multinomial with Complex Cell Structure; 2.5 Example 2.5: Analysis of PET and SPECT Data; 2.6 Example 2.6: Multivariate t-Distribution (Known D.F.); 2.6.1 ML Estimation of Multivariate t-Distribution; 2.6.2 Numerical Example: Stack Loss Data; 2.7 Finite Normal Mixtures; 2.7.1 Example 2.7: Univariate Component Densities; 2.7.2 Example 2.8: Multivariate Component Densities 2.7.3 Numerical Example: Red Blood Cell Volume Data2.8 Example 2.9: Grouped and Truncated Data; 2.8.1 Introduction; 2.8.2 Specification of Complete Data; 2.8.3 E-Step; 2.8.4 M-Step; 2.8.5 Confirmation of Incomplete-Data Score Statistic; 2.8.6 M-Step for Grouped Normal Data; 2.8.7 Numerical Example: Grouped Log Normal Data; 2.9 Example 2.10: A Hidden Markov AR(1) model; 3 BASIC THEORY OF THE EM ALGORITHM; 3.1 Introduction; 3.2 Monotonicity of the EM Algorithm; 3.3 Monotonicity of a Generalized EM Algorithm; 3.4 Convergence of an EM Sequence to a Stationary Value; 3.4.1 Introduction 3.4.2 Regularity Conditions of Wu (1983) |
| Record Nr. | UNINA-9910877999303321 |
|
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Finite mixture models [[electronic resource] /] / Geoffrey McLachlan, David Peel
| Finite mixture models [[electronic resource] /] / Geoffrey McLachlan, David Peel |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | New York, : Wiley, c2000 |
| Descrizione fisica | 1 online resource (450 p.) |
| Disciplina |
519
519.2 519.532 |
| Altri autori (Persone) | PeelDavid <1971-> |
| Collana | Wiley series in probability and statistics. Applied probability and statistics section |
| Soggetto topico |
Mixture distributions (Probability theory)
Mathematics |
| ISBN |
1-280-26492-6
9786610264926 0-470-34190-4 0-471-65406-X 0-471-72118-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contents; Preface; 1 General Introduction; 2 ML Fitting of Mixture Models; 3 Multivariate Normal Mixtures; 4 Bayesian Approach to Mixture Analysis; 5 Mixtures with Nonnormal Components; 6 Assessing the Number of Components in Mixture Models; 7 Multivariate t Mixtures; 8 Mixtures of Factor Analyzers; 9 Fitting Mixture Models to Binned Data; 10 Mixture Models for Failure-Time Data; 11 Mixture Analysis of Directional Data; 12 Variants of the EM Algorithm for Large Databases; 13 Hidden Markov Models; Appendix: Mixture Software; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910143199603321 |
|
McLachlan Geoffrey J. <1946->
|
||
| New York, : Wiley, c2000 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Finite mixture models [[electronic resource] /] / Geoffrey McLachlan, David Peel
| Finite mixture models [[electronic resource] /] / Geoffrey McLachlan, David Peel |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | New York, : Wiley, c2000 |
| Descrizione fisica | 1 online resource (450 p.) |
| Disciplina |
519
519.2 519.532 |
| Altri autori (Persone) | PeelDavid <1971-> |
| Collana | Wiley series in probability and statistics. Applied probability and statistics section |
| Soggetto topico |
Mixture distributions (Probability theory)
Mathematics |
| ISBN |
1-280-26492-6
9786610264926 0-470-34190-4 0-471-65406-X 0-471-72118-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contents; Preface; 1 General Introduction; 2 ML Fitting of Mixture Models; 3 Multivariate Normal Mixtures; 4 Bayesian Approach to Mixture Analysis; 5 Mixtures with Nonnormal Components; 6 Assessing the Number of Components in Mixture Models; 7 Multivariate t Mixtures; 8 Mixtures of Factor Analyzers; 9 Fitting Mixture Models to Binned Data; 10 Mixture Models for Failure-Time Data; 11 Mixture Analysis of Directional Data; 12 Variants of the EM Algorithm for Large Databases; 13 Hidden Markov Models; Appendix: Mixture Software; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910830949803321 |
|
McLachlan Geoffrey J. <1946->
|
||
| New York, : Wiley, c2000 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Finite mixture models / / Geoffrey McLachlan, David Peel
| Finite mixture models / / Geoffrey McLachlan, David Peel |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | New York, : Wiley, c2000 |
| Descrizione fisica | 1 online resource (450 p.) |
| Disciplina | 519.2 |
| Altri autori (Persone) | PeelDavid <1971-> |
| Collana | Wiley series in probability and statistics. Applied probability and statistics section |
| Soggetto topico |
Mixture distributions (Probability theory)
Mathematics |
| ISBN |
1-280-26492-6
9786610264926 0-470-34190-4 0-471-65406-X 0-471-72118-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contents; Preface; 1 General Introduction; 2 ML Fitting of Mixture Models; 3 Multivariate Normal Mixtures; 4 Bayesian Approach to Mixture Analysis; 5 Mixtures with Nonnormal Components; 6 Assessing the Number of Components in Mixture Models; 7 Multivariate t Mixtures; 8 Mixtures of Factor Analyzers; 9 Fitting Mixture Models to Binned Data; 10 Mixture Models for Failure-Time Data; 11 Mixture Analysis of Directional Data; 12 Variants of the EM Algorithm for Large Databases; 13 Hidden Markov Models; Appendix: Mixture Software; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910877772003321 |
|
McLachlan Geoffrey J. <1946->
|
||
| New York, : Wiley, c2000 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||